Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome ...
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in fine-mode aerosols are limited. In this study, we employed newly devel...
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran conside...
Optimal combustion control of untreated landfill gas is proposed for an effective usage and a low-cost solution in waste to energy technologies. Variations of methane concentration in untreated landfill gas over time cause undesired performance of co...
Elemental identification of individual microsized aerosol particles is an important topic in air pollution studies. However, simultaneous and quantitative analysis of multiple constituents in a single aerosol particle with the noncontact in situ mann...
Neural networks : the official journal of the International Neural Network Society
Nov 5, 2020
Air quality prediction is a global hot issue, and PM is an important factor affecting air quality. Due to complicated causes of formation, PM prediction is a thorny and challenging task. In this paper, a novel deep learning model named temperature-ba...
Reliable estimates of outdoor air pollution concentrations are needed to support global actions to improve public health. We developed a new approach to estimating annual average outdoor nitrogen dioxide (NO) concentrations using approximately 20,000...
In this study, we report on the applicability of passive sampling with Carbopack X adsorbent tubes followed by thermal desorption gas-chromatography-mass spectrometry (TD-GC-MS) to monitor the concentrations of emerging organic contaminants (EOCs) an...
INTRODUCTION: Estimating PM concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in nat...
International journal of environmental research and public health
Sep 23, 2020
This paper uses machine learning to refine a Land-use Regression (LUR) model and to estimate the spatial-temporal variation in BTEX concentrations in Kaohsiung, Taiwan. Using the Taiwanese Environmental Protection Agency (EPA) data of BTEX (benzene, ...
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